This command generates the same isolated environment as the other commands, but instead of running your code or dropping you into a shell, runs a local instance of Jupyter based in the folder where you execute the command.
caliban notebook supports the following arguments:
usage: caliban notebook [-h] [--helpfull] [--nogpu] [--cloud_key CLOUD_KEY] [--extras EXTRAS] [--docker_run_args DOCKER_RUN_ARGS] [-p PORT] [-jv JUPYTER_VERSION] [--lab] [--bare] optional arguments: -h, --help show this help message and exit --helpfull show full help message and exit --nogpu Disable GPU mode and force CPU-only. --cloud_key CLOUD_KEY Path to GCloud service account key. (Defaults to $GOOGLE_APPLICATION_CREDENTIALS.) --extras EXTRAS setup.py dependency keys. --docker_run_args DOCKER_RUN_ARGS String of args to add to Docker. -p PORT, --port PORT Port to use for Jupyter, inside container and locally. -jv JUPYTER_VERSION, --jupyter_version JUPYTER_VERSION Jupyterlab version to install via pip. --lab run 'jupyter lab', vs the default 'jupyter notebook'. --bare Skip mounting the $HOME directory; run an isolated Jupyter lab.
caliban notebook runs
jupyter notebook inside the container. To
run Jupyterlab, pass the
caliban notebook --lab
As with the other commands, the only python dependencies available in the container will be dependencies that you declare explicitly in either:
Your setup file can declare groups of dependencies using the setuptools
feature. (See the Declaring Requirements docs for more detail
on how to use
extras_require to create separate environments for GPU and
Mounted Home Directory¶
caliban notebook mounts your
$HOME directory into the container, which
allows your Jupyter settings to persist across sessions. If you don’t want this
for some reason, run the command with the
Custom Jupyer Port¶
If you’d like to run
notebook using a different port, use the
caliban notebook --lab --port 8889
On the Mac you’ll have to pass
notebook, as the NVIDIA runtime
isn’t supported on non-Linux machines.